ArticleNature biotechnology2013
A gene ontology inferred from molecular networks.
Article in Nature biotechnology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 114 papers, 1 of them a synthesis that pooled it.
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Who cites it
114 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Updating genome annotation for the microbial cell factory Aspergillus niger using gene co-expression networks.Nucleic acids research · 2019Pooled it
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- A multi-scale map of protein assemblies in the DNA damage response.Cell systems · 2023Article
- Genomics, convergent neuroscience and progress in understanding autism spectrum disorder.Nature reviews. Neuroscience · 2022Review
- An evidence-based lexical pattern approach for quality assurance of Gene Ontology relations.Briefings in bioinformatics · 2022Article
- Identification of key miRNAs and targeted genes involved in the progression of oral squamous cell carcinoma.Journal of dental sciences · 2022Article
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- Investigation of RNA metabolism through large-scale genetic interaction profiling in yeast.Nucleic acids research · 2021Article
- Genetic dissection of complex traits using hierarchical biological knowledge.PLoS computational biology · 2021Article
- Functional landscape of SARS-CoV-2 cellular restriction.Molecular cell · 2021Article
- Mapping the multiscale structure of biological systems.Cell systems · 2021Review
- Disentangling the Molecular Pathways of Parkinson's Disease using Multiscale Network Modeling.Trends in neurosciences · 2021Review
54 more citing papers are in PubMed but not listed here.
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7 authors.
Funding
Abstract
Ontologies have proven very useful for capturing knowledge as a hierarchy of terms and their interrelationships. In biology a major challenge has been to construct ontologies of gene function given incomplete biological knowledge and inconsistencies in how this knowledge is manually curated. Here we show that large networks of gene and protein interactions in Saccharomyces cerevisiae can be used to infer an ontology whose coverage and power are equivalent to those of the manually curated Gene Ontology (GO). The network-extracted ontology (NeXO) contains 4,123 biological terms and 5,766 term-term relations, capturing 58% of known cellular components. We also explore robust NeXO terms and term relations that were initially not cataloged in GO, a number of which have now been added based on our analysis. Using quantitative genetic interaction profiling and chemogenomics, we find further support for many of the uncharacterized terms identified by NeXO, including multisubunit structures related to protein trafficking or mitochondrial function. This work enables a shift from using ontologies to evaluate data to using data to construct and evaluate ontologies.
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